An attack-resistant hybrid data-privatization method with low information loss
Contribuinte(s) |
Fernandez-Gago, Carmen Martinelli, Fabio Pearson, Siani Augdo, Issac |
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Data(s) |
01/01/2013
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Resumo |
We examine a recent proposal for data-privatization by testing it against well-known attacks, we show that all of these attacks successfully retrieve a relatively large (and unacceptable) portion of the original data. We then indicate how the data-privatization method examined can be modified to assist it to withstand these attacks and compare the performance of the two approaches. We also show that the new method has better privacy and lower information loss than the former method. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Springer |
Relação |
http://dro.deakin.edu.au/eserv/DU:30060714/evid-trustmanagementvii-2013.pdf http://dro.deakin.edu.au/eserv/DU:30060714/singh-attackresistant-2013.pdf http://doi.org/10.1007/978-3-642-38323-6_21 |
Direitos |
2013, Springer |
Palavras-Chave | #data-privatization #information loss #Chebyshev polynomial #spectral filtering #Bayes-estimated data reconstruction #data mining |
Tipo |
Book Chapter |